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Description

Seeduplex represents a cutting-edge full-duplex speech large language model that operates on an innovative “listen while speaking” paradigm to facilitate more natural, fluid, and accurately timed voice interactions. Unlike conventional half-duplex systems that switch between listening and responding, it continually processes and comprehends audio from the user, enabling simultaneous listening and speaking while being aware of the surrounding acoustic environment. Its advanced interference suppression capabilities effectively differentiate genuine user input from background distractions such as noise, broadcasts, navigation cues, and overlapping conversations, thereby minimizing incorrect responses and disruptions in intricate scenarios. Furthermore, Seeduplex integrates both speech and semantic features for dynamic endpoint detection, allowing it to discern when a user is contemplating, pausing, correcting themselves, or has completed their statement. This model exhibits the ability to patiently endure reflective silences, provide swift responses immediately after an utterance concludes, and seamlessly cease speaking when interrupted, ensuring a more engaging interaction. Ultimately, the design of Seeduplex aims to enhance user experience by making voice communication feel more intuitive and responsive.

Description

TML-Interaction-Small is a multimodal interaction model created by Thinking Machines Lab that enables continuous real-time collaboration between humans and AI across audio, video, and text modalities. The model is designed to move beyond traditional turn-based AI systems by supporting native interaction capabilities such as simultaneous listening and speaking, proactive interjections, visual cue awareness, real-time responses, and ongoing contextual collaboration. TML-Interaction-Small processes interactions through a time-aligned micro-turn architecture that continuously exchanges 200ms streams of input and output, allowing the model to maintain conversational presence while reasoning, responding, and acting concurrently. The system combines an interaction model with an asynchronous background model that handles deeper reasoning, tool usage, browsing, and long-running workflows while the primary interaction layer continues communicating with the user in real time. The architecture allows users to collaborate with AI more naturally through speech, video, messaging, and multimodal inputs without waiting for rigid conversational turn boundaries. Thinking Machines Lab developed the model to improve human-AI collaboration by keeping people actively involved during AI workflows rather than relying solely on autonomous agents. TML-Interaction-Small includes capabilities such as live translation, contextual interruptions, visual-based reactions, concurrent speech processing, time awareness, tool calling, web browsing, and multimodal streaming interaction. The system also introduces encoder-free early fusion techniques, streaming inference optimization, and reinforcement learning strategies optimized for interactive responsiveness and stability.

API Access

Has API

API Access

Has API

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Screenshots View All

Integrations

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Integrations

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Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

ByteDance

Founded

2012

Country

China

Website

seed.bytedance.com/en/seeduplex

Vendor Details

Company Name

Thinking Machines Lab

Country

United States

Website

thinkingmachines.ai/

Product Features

Product Features

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